Gazing time analysis for drowsiness assessment using eye gaze tracker

Arthur Mourits Rumagit, Izzat Aulia Akbar, Tomohiko Igasaki*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


From several investigations, it has been shown that most of the traffic accidents were due to drowsy driving. In order to address this issue, many related works have been conducted. One study was able to capture the driver's facial expression and estimate their drowsiness. Instead of measuring the driver's physiological condition, the results of such measurements were also used to predict their drowsiness level in this study. We investigated the relationship between the drowsiness and physiological condition by employing an eye gaze signal utilizing an eye gaze tracker and the Japanese version of the Karolinska sleepiness scale (KSS-J) within the driving simulator environment. The results showed that the gazing time has a significant statistical difference in relation to the drowsiness level: alert (1-5), weak drowsiness (6-7), and strong drowsiness (8-9), with P < 0.001. Therefore, we suggested the potential of using the eye gaze to assess the drowsiness under a driving condition.

Original languageEnglish
Pages (from-to)919-925
Number of pages7
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Issue number2
Publication statusPublished - 1 Jun 2017
Externally publishedYes


  • Driving simulator
  • Drowsiness
  • Eye gaze tracker
  • Gazing time
  • Karolinska sleepiness scale


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